tbuckley/cabot-search huggingface dataset:
NIMG-86. REVEALING THE BIOLOGY BEHIND MRI SIGNATURES IN GLIOBLASTOMA
Authors: Erika Lewis, Nhan Tran, Kristin Swanson, Leland Hu, Christopher Plaisier
Journal: Neuro-Oncology (2022)

Abstract The brain is notoriously difficult to access because of its location and protective mechanisms, both internal and external. Imaging-based approaches, such as multiparametric magnetic resonance imaging (mpMRI), provide a method to bypass these obstacles. mpMRI can capture a wide range of data from tumors embedded in brain tissue through various imaging features. However, the biological function captured by each imaging feature remains largely unknown, particularly within the aggressive disease glioblastoma multiforme (GBM). We integrated our GBM SYstems Genetics Network AnaLysis (gbmSYGNAL) gene regulatory network (Plaisier, et al. 2016), based on the multi-omic patient data from The Cancer Genome Atlas (TCGA), with mpMRI-localized patient tumor biopsies. The gbmSYGNAL network was reconstructed within the new image-localized biopsies, and associations revealed a strong connection between the spoiled gradient recalled echo + contrast (SPGR+C) feature and the immune hallmarks of cancer. The SPGR+C method generates an image by employing a contrast agent that bypasses the blood brain barrier (BBB) through leaky blood vessels that have weakened from the force of the rapidly growing GBM tumor. Furthermore, a significant association between SPGR+C signal and the presence of both infiltrating macrophages and T cells indicated that peripheral immune cells may also cross the BBB at these leaky sites. Separately, the mean diffusivity (MD) &amp; T2 features were linked to the sustained angiogenesis hallmark. These features displayed high association with angiogenic genes, such as FLT1, KDR, and PDGFRB, and correlated with the presence of histologically identified vessels. Detection of these disease-relevant functions via mpMRI features has powerful clinical applications, providing a non-invasive approach to GBM diagnosis, prognosis, and treatment direction.
NIMG-72. VALIDATION OF CONDITIONAL AND SUPER-RESOLUTION GENERATIVE ADVERSARIAL NETWORKS FOR IMPUTATION OF MISSING BRAIN MRI SEQUENCES
Authors: Gian Marco Conte, W Oliver Tobin, Mana Moassefi, Shahriar Faghani, Paul Decker, Matthew Kosel, Yalda Nikanpour, Kuan Zhang, Daniel Honore Lachance, Robert Jenkins, Bradley Erickson, Jeanette Eckel-Passow
Journal: Neuro-Oncology (2022)

Abstract Missing MRI sequences are common in radiology due to differences in protocols, time constraints, and image artifacts. Missing sequences are a nuisance for subsequent algorithms, such as automated segmentation algorithms requiring multiple MRI sequences (e.g., HD-GLIO, which requires T2, T1, post-contrast T1 (T1c), and FLAIR). Accurate tumor segmentation is a fundamental step in extracting radiomics analysis to use, for example, to predict the IDH status of glioma or their overall survival. We validated a conditional (pix2pix) and super-resolution GAN (SOUP-GAN) for imputing MRI sequences on 285 adult glioma with complete MRI sequences available. We simulated missing T1 sequences and subsequently imputed them from T1c using pix2pix and from sagittal T1 using SOUP-GAN. Using HD-GLIO, we obtained the true segmentations from the complete MRI sequences. HD-GLIO was also used after replacing the original T1 sequence with the one imputed with pix2pix and SOUP-GAN. Thus, there were three sets of segmentations for each subject. We compared T2 and T1c radiomics features extracted with Pyradiomics using segmentations obtained with complete data with features extracted from segmentation obtained with the imputed T1 sequences using intraclass correlation coefficient (ICC) and Bland-Altman (BA) analysis. Median (interquartile range) ICC for shape features extracted from T2 and T1c were 0.82(0.76-0.92) using pix2pix and 0.89(0.86-0.94) using SOUP-GAN. Median ICC for first-order-statistics features were 0.90(0.83-0.93) for T2 and 0.90(0.88-0.92) for T1c using pix2pix, and 0.61(0.22-0.82) for T2 and 0.42(0.34-0.57) for T1c using SOUP-GAN. Median ICC for texture features were 0.86(0.82-0.87) for T2 and 0.87(0.79-0.90) for T1c using pix2pix, and 0.69(0.47-0.81) for T2 and 0.76(0.65-0.83) for T1c using SOUP-GAN. We show that T2 and T1c shape features (e.g., volumetric analysis) can be adequately extracted from segmentations obtained with an algorithm requiring multiple MRI sequences using T1 sequences imputed with GANs; however, the effect of imputation differed for first-order-statistics and texture features.
NIMG-74. RADIOIMMUNOMIC SIGNATURES IN PEDIATRIC LOW-GRADE GLIOMA BASED ON MULTIPARAMETRIC MRI SCANS
Authors: Anahita Fathi Kazerooni, Adam A Kraya, Meen Chul Kim, Nastaran Khalili, Sherjeel Arif, Run Jin, Komal Rathi, Ariana Familiar, Rachel Madhogarhia, Debanjan Haldar, Sina Bagheri, Hannah Anderson, Ibraheem Salman Shaikh, Shuvanjan Haldar, Jeffrey B Ware, Arastoo Vossough, Philip B Storm, Adam C Resnick, Christos Davatzikos, Ali Nabavizadeh
Journal: Neuro-Oncology (2022)

Abstract Understanding the immune microenvironment in pediatric low-grade glioma (pLGG) patients may help in identification of the patients who benefit from anti-tumor immunotherapies. However, surgical resection is not feasible for many pLGG tumors in certain anatomical locations. Therefore, developing non-invasive tools that characterize the tumor microenvironment prior to therapeutic interventions could contribute to stratification and enrollment of the patients into relevant clinical trials. In this work, we derived radiomic signatures of immune profiles (radioimmunomics) based on machine learning (ML) analysis of readily available conventional MRI scans. Transcriptomic data for a cohort of 197 subjects was retrospectively collected from Open Pediatric Brain Tumor Atlas (OpenPBTA). The patients were categorized into three groups (Group1-3) based on their immunological profiles using consensus clustering algorithm. This analysis revealed greater immune cell infiltration in non-BRAF mutated pLGGs. Group1 showed more enrichment in M1 macrophages, and microenvironment and immune scores compared to Group2 and Group3. Elevated tumor inflammation score (TIS), as a predictor of clinical response to anti-PD-1 blockade, was observed in Group1 compared to Group2 (p= 1.4e-7) and Group3 (p= 0.0054). Radiomic features, including volumetric, morphologic, histogram, and texture descriptors, were extracted from the segmented tumor regions on multiparametric MRI (mpMRI) scans of 71 (of 197) patients. Multivariate ML models were trained to predict the three immunological groups based on radiomic features using cross-validated random forest classifier along with recursive feature elimination, which yielded AUC of 0.72 for this multi-class classification problem. Our findings indicate the presence of distinct immunological groups in pLGG tumors, with possibly more favorable response to immunotherapies in Group1 tumors. Furthermore, we developed radioimmunomic signatures based on pre-operative conventional mpMRI that can potentially stratify the patients based on their immune tumor microenvironment. Based on these initial promising results, we are exploring additional features to increase the accuracy of radioimmunomics model.
EXTH-46. RNA LIPID PARTICLES INDUCE BI-DIRECTIONAL IMMUNITY AGAINST DIFFUSE MIDLINE GLIOMA
Authors: James McGuiness, Frances Weidert, Dingpeng Zhang, Adam Grippin, Aida Karachi, Sadeem Qdaisat, Nagheme Thomas, Paul Castillo, Jianping Huang, John Ligon, Natalie Silver, Maryam Rahman, Eugene Hwang, Duane Mitchell, Hector Mendez-Gomez, Elias Sayour
Journal: Neuro-Oncology (2022)

Abstract BACKGROUND Diffuse Intrinsic Pontine Glioma (DIPG) is uniformly fatal. Upon diagnosis, DIPG cannot be safely debulked and systemic therapies have unproven benefit. Immunotherapy can overcome these obstacles, but objective responses are rare; and cancer antigens, even when tumor specific (i.e. H3K27M), are usually poorly immunogenic. OBJECTIVE We sought to develop a murine model of diffuse midline glioma (DMG) that better recapitulates human disease. In these models, we tested different iterations of mRNA loaded nanoparticle (NP) vaccines for their therapeutic effect. APPROACH: We implanted murine gliomas (expressing H3K27M mutation) midline into developing neonatal brains. We manufactured different mRNA constructs encoding for foreign proteins (e.g. GFP), H3K27M or wildtype H3K27 and evaluated immunogenicity and anti-tumor efficacy. These mRNA vaccines were layered into lipid particles (RNA-NP) and administered intravenously when animals became acutely symptomatic (similar to when patients are diagnosed). RESULTS Surprisingly, all mRNA constructs tested were sufficient to elicit anti-tumor efficacy against DMGs. This was true for both antigen specific (H3K27M) and non-antigen specific constructs (GFP, H3K27 wildtype). While H3K27M encoding RNA-NPs were superior to H3K27 wildtype encoding RNA-NPs (p=0.057), the adaptive immune effects appear marginal relative to the innate immune responses generated by all RNA-NP constructs. These innate responses are characterized by induction of type I interferon response from plasmacytoid DCs. Interestingly, these effects could not be recapitulated in murine models of adult type glioblastoma (KR158b) which required antigen specificity for induction of anti-tumor efficacy. CONCLUSION These data suggest that pediatric gliomas may be particularly sensitive to innate immunity. We have optimized development of a target H3K27M mRNA construct that balances innate and adaptive bi-directional immune induction. We are completing FDA-IND enabling data to support translation of H3K27M loaded RNA-NPs into human clinical trials.
INNV-03. THE YIELD OF SCREENING MRI AMONG STAGE IV NON SMALL CELL LUNG CANCER PATIENTS
Authors: Efraim Waizman, Inbar Lavie, Alexandra Amiel, Tali Siegal, Elizabeth Dudnick, Shlomit Yust-Katz
Journal: Neuro-Oncology (2022)

Abstract BACKGROUND Brain metastases are a common complication of non small cell lung cancer (NSCLC). Approximately 10 percent of newly diagnosed patients with advanced NSCLC have brain metastases. The purpose of this study was to determine whether using magnetic resonance imaging (MRI) for early screening of brain metastases can improve survival. Material and METHODS A retrospective analysis of newly diagnosed stage IV NSCLC treated at Davidoff Cancer Center, Israel, between the years 2019-2020. Only patients who were neurologically asymptomatic were included in the study. The study population was divided into two groups. Group A included patients who underwent screening MRI within 12 weeks form diagnosis and group B included those who did not undergo screening MRI. Clinical and radiographic data were collected form the medical records. RESULTS 379 patients were included in the study, of whom 170 underwent screening MRI. Of the patients who underwent screening MRI 54 were diagnosed with brain metastases. On univariate analysis screening MRI was corelated with better survival [group A median survival 24 month, group B median survival 18 month, p=0.003 HR 1.4 CI 1.12-1.75]. On multivariate analysis that included functional status (ECOG 0-2 compared to 3 and above) and age- screening MRI corelated with survival (p=0.04 HR 1.28 CI 1.02-1.6). Subgroup analysis according to molecular subgroup will be presented in the conference. CONCLUSION In this study screening MRI among stage IV NSCLC correlated with better survival even when adjusted to functional status and age.
BIOM-56. MIR-497 AND 219 IN BLOOD AID MENINGIOMA CLASSIFICATIONMIR-497 AND 219 IN BLOOD AID MENINGIOMA CLASSIFICATION
Authors: Clemens Oliver Hanemann, Ahmed Abdelrahman, Claire Adams, Felix Sahm, Tadeja Urbanic-Purkart, Michael Khalil, Raffaella Vergura, Cristina Morelli
Journal: Neuro-Oncology (2022)

Abstract There is a need for blood biomarkers for meningioma. The role of circulating micro RNA in cancer diagnosis has been the objective of several studies. One of the extensively studied miRNA in different types of cancer is the microRNA-497 (miR-497). This study systematically evaluated miR-497 as a meningioma biomarker for disease diagnosis and classification. We studied exosomal and serum miR-497 in 74 meningioma samples (WHO grade I=25, WHO grade II=25, and WHO grade III=24), and 53 healthy controls. We also tested two different normalisers, endogenous and external, and evaluated their impact on the diagnostic value of miR-497. Another microRNA studied in meningioma is miR-219, which increased with increasing tumour grade. We combined miR-497 and miR-219 and estimated the sensitivity and specificity of the joint biomarkers to indicate meningioma grade and the relationship between miR-497 and miR-219 expression level and methylation class of meningioma. The serum and exosomal level of miR-497 distinguished meningioma from the control samples. Moreover, miR-497 was a suitable identifier for meningioma grade. When we combined miR-497 and miR-219, the efficacy of the combined biomarker was higher than miR-497 or miR-219 when used individually in meningioma classification. Both miR-497 and miR-219 showed a noticeable change with the methylation class of meningioma.
CSIG-12. BXQ-350 INDUCES MITOPHAGY IN GBM CELLS LEADING TO CELL DEATH
Authors: Nikhil Wilkins, Robin Furnish, Tim Stephens
Journal: Neuro-Oncology (2022)

Abstract BACKGROUND Mitophagy is an autophagic phenomenon where defective mitochondria are selectively degraded. When mitochondria need recycling, the cell upregulates the production of the lipid C-18 ceramide on the mitochondria and lipoprotein LC3B-II on the lysosome, which transitions to an autophagolysosome. This creates a signal causing the degradation of mitochondria. Here we show that BXQ-350, a novel protein-lipid small molecule consisting of the ceramide creating protein Saposin C and the lipid Dioleoyl Phosphatidylserine (DOPS), induces glioblastoma cells into performing mitophagy. Increased production of mitophagy associated proteins, C-18, and LC3B-II leads to the degradation of healthy mitochondria followed by cell death. METHODS The GBM cell lines, Gli36 and U87 cells, were used to determine if increased mitophagy was occurring in response to BXQ-350 treatment. Protein abundance was measured using SILAC proteomics. Ceramide levels were analyzed using LC/MS-MS. Western Blot analysis was used to measure differences in LC3B-II levels. Mitophagy was measured using Mtphagy Dye from Dojindo and the BioTek Cytation 5 microscope. RESULTS Proteomics showed cells treated with BXQ-350 had an increase in proteins associated with overexpression of C-18 ceramide or autophagolysosome maturation. Western blots analysis showed a marked increase in LC3B-II in BXQ-350 treated cells. Furthermore, cells treated with BXQ-350 had increased levels of C-18 ceramide. The Mtphagy dye showed that as BXQ-350 concentrations increased, the percentage of cells positive for Mitophagy increased. To determine if mitophagy occurs in association with BXQ-350 cytotoxicity, medias with varying BXQ-350 cytotoxicity were used. The Mtphagy dye showed cytotoxic BXQ-350 medias increased levels of mitophagy, while noncytotoxic medias display no increase in mitophagy. CONCLUSION BXQ-350 causes the increase of mitophagy signaling proteins, C-18 ceramide and LC3B-II production, resulting in the formation of autophagolysosomes which track towards the mitochondria initiating mitophagy. This leads to aberrant mitophagy where cells degrade healthy mitochondria leading to mitophagic cell death.
NIMG-66. CANNY EDGE DETECTION ALGORITHM FOR QUANTITATIVE DIFFERENTIATION BETWEEN DIFFUSE AND CIRCUMSCRIPT GLIOMA GROWTH PATTERNS ON MRI
Authors: Frederic Thiele, Jonathan Weller, Sophie Katzendobler, Christoph Trumm, Niklas Thon, Joerg-Christian Tonn
Journal: Neuro-Oncology (2022)

Abstract BACKGROUND Lower grade gliomas show heterogenous appearance on T2-weighted MRI. Some tumors grow diffusely along axonal structures whereas others distort adjacent brain tissue through local mass effect. The diagnostic, therapeutic and prognostic implication of differential growth patterns on MRI remain unknown and are difficult to assess quantitatively. METHODS A web-based application allowing for image preprocessing and providing a comprehensive edge detection tool by means of quantifying tumor border delineation on T2-weighted images based on the canny edge detection algorithm was developed. A sigma value between 1 and 100 determined the threshold where tumor borders where not detected anymore, with 1 equating to the lowest threshold and thus detection of all edges contained in the image. Two experienced faculty members assigned sigma values to axial T2 images of a random sample of 20 WHO grade 2 astrocytomas, IDH-mutant and 1p/19q-non-codeleted. The sigma values were then compared with a binary, subjective rating by the same faculty staff according to the perceived predominant growth pattern (diffuse versus circumscript) of each glioma. RESULTS When subjectively categorizing tumors binarily (diffuse versus circumscript), there was moderate interrater variability between observers (cohen’s kappa=0.6). Raters agreed in 16 of 20 cases, terming 7 gliomas unanimously diffuse and 9 gliomas circumscript. In 4 cases, the raters opinions diverged. The sigma values differed significantly between diffuse and circumscript tumors in both raters (rater 1, p=0.002; rater 2, p=0.018). For rater 1, the mean sigma difference between diffuse and circumscript tumors was 10.7 and 9.3 for rater 2. The mean overall sigma value was 13.3 for rater 1 and 18.7 for rater 2 (p=0.005). CONCLUSION Edge detection algorithms can be efficiently applied on MRI scans and are highly accurate in differentiating diffuse from circumscript gliomas. Objectification demands defining imaging criteria for diffuse and circumscript appearance of lower grade gliomas on MRI.
PATH-11. THE LONGITUDINAL EVOLUTIONARY TRAJECTORY OF OLIGODENDROGLIOMA IS DRIVEN BY TREATMENT-ASSOCIATED GENETIC ALTERATIONS
Authors: Frederick Varn, Gordon Ye, Padmaja Ghospurkar, Taylor Wade, Mustafa Khasraw, Eric S Lipp, Beth Hermes, Carol Elliott, Joseph F Costello, Chibo Hong, Pim French, Wies Vallentgoed, Marta Padovan, Ho-Keung Ng, Kay Li, Hui Gan, Kerryn Westcott, Rachael Vaubel, Craig Horbinski, Kathleen McCortney, Sun Ha Paek, Hyo-Eun Moon, Peter LaViolette, Allison Lowman, Jill Barnholtz-Sloan, Pieter Wesseling, Roel Verhaak
Journal: Neuro-Oncology (2022)

Abstract Oligodendroglioma is a subtype of diffuse glioma defined by a mutation in the isocitrate dehydrogenase (IDH) genes and a co-deletion of chromosome arms 1p and 19q. These tumors primarily occur in adult patients in their third and fourth decade of life and are universally fatal due to an inevitable recurrence that follows a treatment regimen of surgical resection and an optional combination of alkylating chemotherapy and/or radiation therapy. While initially slow growing, recurrent tumors exhibit increasingly aggressive phenotypes that become progressively more difficult to treat with conventional therapy. Currently, the molecular mechanisms and cellular phenotypes that drive this recurrence remain unknown. To understand these factors, we assembled a cohort of matched initial and recurrent oligodendroglioma samples from over 100 patients and performed whole-genome sequencing and whole-exome sequencing on each of them. To link these molecular profiles to cell state changes, we additionally performed bulk and single-nucleus RNA-sequencing on a subset of these tumor pairs. In nearly 40% of alkylating chemotherapy-treated patients, recurrent tumors presented with hypermutation that corresponded with an increase in neoplastic cell proliferation. Additionally, while individual somatic alterations specific to recurrence were relatively rare, we observed a subset of tumors that acquired deletions in the cell cycle regulator CDKN2A following treatment with radiotherapy. Acquisition of either of these features associated with shorter patient survival and higher grade at recurrence, implicating cell cycle dysregulation as a mechanism of treatment resistance and increased tumor severity. Together, these results indicate that oligodendrogliomas evolve in a treatment-specific manner following chemo- and radiation therapy and highlight key pathways that can be targeted to delay the onset of recurrence.
NIMG-09. BRAIN METASTASIS FROM PANCREATIC CANCER: OUR EXPERIENCE AND SYSTEMATIC REVIEW
Authors: Frank Destefano, Alexis Morell, Katya Marks, Sophia Fernandez, Timothy Mayo, Grace Smith, Martin Merenzon, Ashish Shah, Evan Luther, Michael Ivan, Ricardo Komotar, Daniel Eichberg
Journal: Neuro-Oncology (2022)

Abstract BACKGROUND AND PURPOSE The goal of this study was to systematically review the existing literature on neurosurgical management and outcomes of brain metastasis from pancreatic cáncer in comparison to our institutional experience of this patient cohort. METHODS Following the PRISMA guidelines, a systematic literature review was performed using PubMed, Ovid Embase, Scopus, and Web of Science databases from date of database inception to January 2022. Studies were selected based on predetermined inclusion and exclusión criteria. Simulteanously, a retrospective analysis was conducted on patients who underwent neurosurgical evaluation and treatment for intracranial metastatic lesions from pancreatic origin at a single institution. RESULTS Of the total 292 articles in the original literature search, 17 studies were ultimately selected. A total of 23 patients with brain metastases of pancreatic origin were included. Median overall survival from original diagnosis of pancreatic cancer was 22 months (3-84). In our institution’s cohort, 4 patients were identified with a median overall survival of 30.5 months (2- 108). Our institutional cohort experienced a prolonged median overall survival (3 vs 30.5 months, p=0.03) in comparison to the literature. CONCLUSIONS Brain metastasis is a rare and fatal outcome of pancreatic cancer that carries a poor survival. However, based on the data presented in this review, there are patient-specific and treatment-related factors that could signal better prognosis. Further studies are needed to elucidate multimodal therapy and survival to suggest a more personalized decision-making process.